000			02060nam a22002657a 4500
999			_c8840 _d8840
001			WIIW0000169
003			OSt
005			20190802143607.0
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008			190802t2018 |||||q|||||00| 0 eng d
020			_a978-1-4920-3871-9
040			_cOSt
041			_aeng
100	1		_aMalaska, Ted _4aut
245	1	0	_aFoundations for architecting data solutions. _bManaging successful data projects
250			_aFirst edition
260	1		_aBeijing _aBoston _aFarnham _aSebastopol _aTokyo _bO'Reilly _cSeptember 2018
300			_aXII, 173 S.
500			_aIncludes index.
520			_aWhile many companies ponder implementation details such as distributed processing engines and algorithms for data analysis, this practical book takes a much wider view of big data development, starting with initial planning and moving diligently toward execution. Authors Ted Malaska and Jonathan Seidman guide you through the major components necessary to start, architect, and develop successful big data projects. Everyone from CIOs and COOs to lead architects and developers will explore a variety of big data architectures and applications, from massive data pipelines to web-scale applications. Each chapter addresses a piece of the software development life cycle and identifies patterns to maximize long-term success throughout the life of your project. Start the planning process by considering the key data project types. Use guidelines to evaluate and select data management solutions. Reduce risk related to technology, your team, and vague requirements. Explore system interface design using APIs, REST, and pub/sub systems. Choose the right distributed storage system for your big data system. Plan and implement metadata collections for your data architectureUse data pipelines to ensure data integrity from source to final storage. Evaluate the attributes of various engines for processing the data you collect.
650			_aData Analyses & Machine Learning
700	1		_aSeidman, Jonathan _4aut
942			_cE